[1]许　万,肖　迪,陈婷薇.基于数据驱动的范数最优迭代学习控制[J].湖北工业大学学报,2024,39(2):1-04,16.
　XU Wan,XIAO Di,CHEN Tingwei.Research on Norm Optimal Iterative Learning Control Based on Data Driven[J].,2024,39(2):1-04,16.
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基于数据驱动的范数最优迭代学习控制()
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《湖北工业大学学报》[ISSN:1003-4684/CN:42-1752/Z]

卷:
39
期数:
2024年第2期
页码:
1-04,16
栏目:
出版日期:
2024-04-20

文章信息/Info

Title:
Research on Norm Optimal Iterative Learning Control Based on Data Driven
文章编号:
1003-4684(2024)02 0001 04
作者:
许　万; 肖　迪; 陈婷薇
湖北工业大学机械工程学院,湖北 武汉 ４３００６８
Author(s):
XU Wan; XIAO Di ; CHEN Tingwei
School of Mechanical Engineering, Hubei Univ. of Tech., Wuhan 430068,China
关键词:
迭代学习; 数据驱动; 范数最优; 运动控制
Keywords:
iterative learning;  data drive;  norm optimal;  motion control
分类号:
TP273.1
文献标志码:
A
摘要:
在系统模型确定的前提下,传统的范数最优迭代学习控制(NOILC)可以有效提高伺服系统的跟踪精度.但是在实际控制过程中,系统模型参数往往是变化的,从而导致控制器性能的下降.为此,提出了一种基于数据驱动的范数最优迭代学习控制方法.以系统的输入输出为依据,建立系统估计模型的代价函数,对代价函数进行偏微分处理,得到一种基于数据驱动的非参数模型辨识方法,最后将此模型辨识方法和 NOILC相结合.实验结果表明:针对时变系统,此控制方法的跟踪误差为 NOILC(Normoptimaliterativelearningcontrol,NOILC)的５７．１％,并且相比 NOILC提前５次收敛.因此,提出的方法能有效改善时变系统的跟踪性能.
Abstract:
The traditional norm optimal iterative learning control ( NOILC ) can effectively improve the tracking accuracy of the servo system under the premise of determining the system model. However, in the actual control process, the system model parameters are often changed, resulting in a decline in the performance of the controller. Therefore, a datadriven normoptimal iterative learning control method is proposed. Firstly, based on the input and output of the system, the cost function of the system estimation model is established. Then, the cost function is processed by partial differential, and a datadriven nonparametric model identification method is obtained. Finally, the model identification method is combined with NOILC. The experimental results show that for the timevarying system, the tracking error of this control method is 57.1 % of NOILC, and it converges five times ahead of NOILC. Therefore, the proposed method can effectively improve the tracking performance of timevarying systems.

参考文献/References:

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备注/Memo

备注/Memo:
[收稿日期]２０２２ -０５- ０４[基金项目]中央军委装发部装备预研基金(６１４２２０４２００７０９)[第一作者] 许　万(１９７９－)男,湖北武汉人,湖北工业大学教授,研究方向为运动控制、移动机器人.
更新日期/Last Update: 2024-05-07